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[MLIR][Conversion] XeGPU to XeVM: Remove unused type converter source materializations. #162947

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Merged
merged 2 commits into from
Oct 15, 2025
Merged

[MLIR][Conversion] XeGPU to XeVM: Remove unused type converter source materializations. #162947

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02bd06c
Remove unused type converter source materializations.
silee2 Oct 10, 2025
563a488
Address reviewer comments.
silee2 Oct 13, 2025
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32 changes: 27 additions & 5 deletions mlir/lib/Conversion/XeGPUToXeVM/XeGPUToXeVM.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -20,6 +20,7 @@
#include "mlir/Dialect/MemRef/IR/MemRef.h"
#include "mlir/Dialect/SCF/IR/SCF.h"
#include "mlir/Dialect/SCF/Transforms/Patterns.h"
#include "mlir/Dialect/Vector/IR/VectorOps.h"
#include "mlir/Dialect/XeGPU/IR/XeGPU.h"
#include "mlir/Pass/Pass.h"
#include "mlir/Support/LLVM.h"
Expand Down Expand Up @@ -389,7 +390,8 @@ class LoadStoreToXeVMPattern : public OpConversionPattern<OpType> {
// Load result or Store valye Type can be vector or scalar.
Type valOrResTy;
if constexpr (std::is_same_v<OpType, xegpu::LoadGatherOp>)
valOrResTy = op.getResult().getType();
valOrResTy =
this->getTypeConverter()->convertType(op.getResult().getType());
else
valOrResTy = adaptor.getValue().getType();
VectorType valOrResVecTy = dyn_cast<VectorType>(valOrResTy);
Expand Down Expand Up @@ -879,10 +881,30 @@ struct ConvertXeGPUToXeVMPass
}
return {};
};
typeConverter.addSourceMaterialization(memrefMaterializationCast);
typeConverter.addSourceMaterialization(ui64MaterializationCast);
typeConverter.addSourceMaterialization(ui32MaterializationCast);
typeConverter.addSourceMaterialization(vectorMaterializationCast);

// If result type of original op is single element vector and lowered type
// is scalar. This materialization cast creates a single element vector by
// broadcasting the scalar value.
auto singleElementVectorMaterializationCast =
[](OpBuilder &builder, Type type, ValueRange inputs,
Location loc) -> Value {
if (inputs.size() != 1)
return {};
auto input = inputs.front();
if (input.getType().isIntOrIndexOrFloat()) {
// If the input is a scalar, and the target type is a vector of single
// element, create a single element vector by broadcasting.
if (auto vecTy = dyn_cast<VectorType>(type)) {
if (vecTy.getNumElements() == 1) {
return vector::BroadcastOp::create(builder, loc, vecTy, input)
.getResult();
}
}
}
return {};
};
typeConverter.addSourceMaterialization(
singleElementVectorMaterializationCast);
typeConverter.addTargetMaterialization(memrefMaterializationCast);
typeConverter.addTargetMaterialization(ui32MaterializationCast);
typeConverter.addTargetMaterialization(ui64MaterializationCast);
Expand Down
29 changes: 23 additions & 6 deletions mlir/test/Conversion/XeGPUToXeVM/loadstoreprefetch.mlir
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Expand Up @@ -14,19 +14,36 @@ gpu.func @load_gather_i64_src_value_offset(%src: i64, %offset: vector<1xindex>)
// CHECK: %[[VAR4:.*]] = arith.addi %[[ARG0]], %[[VAR3]] : i64
// CHECK: %[[VAR5:.*]] = llvm.inttoptr %[[VAR4]] : i64 to !llvm.ptr<1>
// CHECK: %[[VAR6:.*]] = scf.if %[[VAR2]] -> (f16) {
// CHECK: %[[VAR7:.*]] = llvm.load %[[VAR5]] {cache_control = #xevm.load_cache_control<L1c_L2uc_L3uc>} : !llvm.ptr<1> -> vector<1xf16>
// CHECK: %[[VAR8:.*]] = vector.extract %[[VAR7]][0] : f16 from vector<1xf16>
// CHECK: scf.yield %[[VAR8]] : f16
// CHECK: } else {
// CHECK: %[[CST_0:.*]] = arith.constant dense<0.000000e+00> : vector<1xf16>
// CHECK: %[[VAR7:.*]] = vector.extract %[[CST_0]][0] : f16 from vector<1xf16>
// CHECK: %[[VAR7:.*]] = llvm.load %[[VAR5]] {cache_control = #xevm.load_cache_control<L1c_L2uc_L3uc>} : !llvm.ptr<1> -> f16
// CHECK: scf.yield %[[VAR7]] : f16
// CHECK: } else {
// CHECK: %[[CST_0:.*]] = arith.constant 0.000000e+00 : f16
// CHECK: scf.yield %[[CST_0]] : f16
// CHECK: }
%3 = xegpu.load %src[%offset], %1 <{l1_hint = #xegpu.cache_hint<cached>, l2_hint = #xegpu.cache_hint<uncached>}>
: i64, vector<1xindex>, vector<1xi1> -> vector<1xf16>
gpu.return
}
}

// -----
gpu.module @test {
// CHECK-LABEL: @source_materialize_single_elem_vec
// CHECK-SAME: %[[ARG0:.*]]: i64, %[[ARG1:.*]]: vector<1xindex>, %[[ARG2:.*]]: memref<1xf16>
gpu.func @source_materialize_single_elem_vec(%src: i64, %offset: vector<1xindex>, %dst: memref<1xf16>) {
%1 = arith.constant dense<1>: vector<1xi1>
%3 = xegpu.load %src[%offset], %1 <{l1_hint = #xegpu.cache_hint<cached>, l2_hint = #xegpu.cache_hint<uncached>}>
: i64, vector<1xindex>, vector<1xi1> -> vector<1xf16>
// CHECK: %[[VAR_IF:.*]] = scf.if
// CHECK: %[[VAR_RET:.*]] = vector.broadcast %[[VAR_IF]] : f16 to vector<1xf16>
// CHECK: %[[C0:.*]] = arith.constant 0 : index
// CHECK: vector.store %[[VAR_RET]], %[[ARG2]][%[[C0]]] : memref<1xf16>, vector<1xf16>
%c0 = arith.constant 0 : index
vector.store %3, %dst[%c0] : memref<1xf16>, vector<1xf16>
gpu.return
}
}

// -----

gpu.module @test {
Expand Down